Javier Hormigo

604 citations
48 papers · 397 indexed · h-index 12

Impact in

Papers in

Javier Hormigo

45 papers receiving 371 citations

Peers

Javier Hormigo
Comparison fields: 5 of 38
  • Hardware and Architecture 121
  • Signal Processing 179
  • Computational Theory and Mathematics 206
  • Computer Vision and Pattern Recognition 85
  • Media Technology 27
Replace Sau-Gee Chen with:
Sau-Gee Chen Taiwan
Shousheng He Sweden
Peter Kornerup Denmark
Khalid H. Abed United States
Jiun-In Guo Taiwan
R. Siferd United States
Yun-Nan Chang Taiwan
Tze‐Yun Sung Taiwan
David Boland Australia
H. Nussbaumer Switzerland
Javier Hormigo relative to Sau-Gee Chen Taiwan Sau-Gee Chen's profile →
Citations per field
00.5×3.4×
Sau-Gee Chen · 1×
Citations per year

Countries citing papers authored by Javier Hormigo

Since Specialization
Citations

This map shows the geographic impact of Javier Hormigo's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Javier Hormigo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Javier Hormigo more than expected).

Fields of papers citing papers by Javier Hormigo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Javier Hormigo. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Javier Hormigo. The network helps show where Javier Hormigo may publish in the future.

Co-authors

The 19 scholars most cited alongside Javier Hormigo, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Javier Hormigo Line = papers co-authored together Javier Hormigo links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20244
2 20233
3 20210
4 20203
5 20196
6 20189
7 20186
8 201541
9 201517
10 20157
11 20120
12 201218
13 20101
14 20093
15 20074
16 200410
17 20043
18 20022
19 20011
20 199822

About Javier Hormigo

Javier Hormigo is a scholar working on Hardware and Architecture, Signal Processing, Computational Theory and Mathematics, Media Technology and Computer Vision and Pattern Recognition, having authored 48 papers that have together received 397 indexed citations. Recurring topics across this work include Numerical Methods and Algorithms (30 papers), Digital Filter Design and Implementation (22 papers), Low-power high-performance VLSI design (16 papers), Parallel Computing and Optimization Techniques (15 papers), Embedded Systems Design Techniques (5 papers), Model Reduction and Neural Networks (4 papers), Image and Signal Denoising Methods (3 papers) and Advanced Data Compression Techniques (3 papers). The work is most often cited by research in Hardware and Architecture (121 citations), Signal Processing (179 citations), Computational Theory and Mathematics (206 citations), Computer Vision and Pattern Recognition (85 citations) and Media Technology (27 citations). Javier Hormigo has collaborated with scholars based in Spain, United States and Uruguay. Frequent co-authors include Julio Villalba, Emilio L. Zapata, Gabriel Cristóbal, Miguel Á. Alfonso‐Sánchez, Andrés Rodríguez, Tomás Lang, Joaquín Olivares, Francisco J. Quiles, Michael Schulte and Jesús Prades. Their work appears in journals such as IEEE Transactions on Computers, IEEE Transactions on Circuits & Systems II Express Briefs, IEEE Transactions on Circuits and Systems I Regular Papers, IEEE Transactions on Very Large Scale Integration (VLSI) Systems and ACM Transactions on Reconfigurable Technology and Systems.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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